In June 2023, our founder and CEO Joe Giovannoli gave a presentation at the Maryland State Bar Association’s annual legal summit regarding AI and its uses in law firm SEO. Below is a recap of his presentation.

What is AI?

Artificial Intelligence (AI) refers to the simulation of human intelligence in machines that are programmed to think and learn like humans. AI encompasses a wide range of technologies, algorithms, and approaches that enable computers or machines to perform tasks that typically require human intelligence, such as perception, reasoning, learning, problem-solving, and decision-making.

AI can be categorized into two main types– narrow AI and general, or strong, AI.

• Narrow AI refers to AI systems that are designed to perform specific tasks within a limited domain, such as voice recognition, image classification, or recommendation systems. Chat GPT is Narrow AI.
• General AI refers to AI systems that possess human-like intelligence and can understand, learn, and perform any intellectual task that a human being can do. In order to be considered Strong AI, it must pass the Turing Test, a test designed to assess a machine’s ability to exhibit intelligent behavior that is indistinguishable from that of a human.

AI systems are designed to analyze vast amounts of data in a short period of time, and to recognize patterns based on the data it takes in. The systems then make predictions or take actions based on the information they process.

This processing often involves techniques like machine learning, natural language processing, and computer vision.

How Does AI Learn?

We all know that AI grows by taking in and synthesizing information. But what does that look like in practice?

• Labeled Datasets – AI models often require large amounts of labeled data to learn and make accurate predictions. Data can be manually labeled by human annotators or obtained from existing labeled datasets. These datasets may include images, text, audio, or video data, depending on the AI task.
• Unlabeled Data – Unlabeled data, also known as raw or unstructured data, is another valuable source for AI learning. Unlabeled data can be collected from various sources such as websites, social media, sensor networks, or public repositories. AI algorithms can analyze and extract patterns from this data to discover insights or perform unsupervised learning.
• User Interactions – AI systems that interact with users, such as virtual assistants or chatbots, can gather data from user interactions. These systems learn from user queries, feedback, and behavior patterns to improve their responses and provide more accurate and personalized assistance.
• Sensor Data – AI systems integrated with sensors, such as those used in autonomous vehicles or IoT devices, can collect data from the physical environment. This sensor data provides information about the surroundings, which helps AI models make decisions or adapt to changing conditions.
• Existing Knowledge Repositories – AI models can be trained using existing knowledge repositories, such as academic papers, books, or publicly available datasets. These sources provide foundational information for learning and enable AI systems to understand and generate new knowledge.
• Enterprise Data – Within organizations, AI systems can leverage internal data sources, including customer records, transaction data, employee data, or operational data. This data can be used for tasks like predictive analytics, recommendation systems, or process optimization.

Marketing Uses for AI

Types of AI tools for use in marketing include conversational AI chatbots, predictive analytics platforms, content generation tools, social media management platforms, personalization engines, voice search optimization tools, and marketing automation platforms. Implementing some of these into your law firm’s website, particularly those that automate marketing and social media and interact with your audience like chatbots, can have a positive impact on your website’s success with limited oversight from your team.

AI and SEO

SEO, or Search Engine Optimization, is the practice of optimizing a website or online content to increase its visibility and ranking on search engine results pages (SERPs). In simpler terms, it involves making strategic adjustments to your online presence so that when people search for relevant keywords or phrases related to your legal services, your website appears higher in the search results. It’s worthwhile for law firms to leverage SEO in order to promote brand awareness for the firm and its attorneys, demonstrate their subject matter expertise, contribute to lead generation, grow the firm’s revenue, and enter new marketing realms.

There are several current AI systems that could be valuable for law firm websites to utilize. For example, Google’s RankBrain is an AI algorithm developed by Google that helps process search queries and analyze user behavior to improve search results. It uses machine learning to understand the intent behind search queries and deliver more relevant results. Another major SEO factor is content, and Yoast SEO is a WordPress plugin that incorporates AI-driven analysis to optimize content for search engines. It provides real-time suggestions and recommendations to improve on-page SEO factors such as keyword usage, readability, meta tags, and more.

A favorite of our SEO team, SEMrush is an all-in-one SEO tool that utilizes AI to provide insights on keyword research, competitor analysis, backlink analysis, content optimization, and more. It offers features like SEO writing assistant, content template recommendations, and position tracking.

These are just a few of the many AI-influenced options that are emerging for law firm SEO use. All of this being said, AI is not a cure-all, nor does it function well without oversight. AI is only as good as the inputs, and it doesn’t take the place of an expert. It’s vital to understand your intended outcome before prompting AI, and not to trust the AI results blindly– confirm the approach by doing independent research.

Law Firm AI Tools

There are several tools available to law firms right now that seek to perform specific tasks for law firms through the assistance of AI. Some of those tools include:

• Contract Analysis Tools – These tools use natural language processing (NLP) and machine learning algorithms to analyze and extract key information from contracts, including provisions, clauses, and obligations. Examples of this include Kira Systems, eBrevia, and Seal Software.
• Predictive Analytics Tools – These tools leverage AI algorithms to analyze large amounts of legal data and make predictions about case outcomes, judge behavior, and legal strategies. Examples include Lex Machina, Ravel Law, and Premonition.
• Legal Research Tools – AI-powered legal research tools can quickly search through vast databases of legal documents, cases, and statutes to provide relevant and up-to-date information for lawyers. Examples include ROSS Intelligence, Westlaw Edge, and Fastcase.
• Document Automation Tools – These tools use AI to automate the creation and generation of legal documents, such as contracts, wills, and legal forms. They can save time and reduce errors in document preparation. Examples of these tools include Contract Express, Documate, and HotDocs.
• E-Discovery Tools – E-discovery tools use AI to assist with the process of reviewing and analyzing electronic documents and data during litigation. They can help identify relevant information, categorize documents, and streamline the review process. Examples include Relativity, Everlaw, and Catalyst.

Moving Forward with AI for Your Law Firm

In this new age of AI, it can be complicated to determine what the right course of action is for your law firm. It seems that there’s a new option every day, and it can feel overwhelming to know which systems to trust. Having 9Sail as your trusted SEO partner can make the transition to AI integration smoother. Reach out to us today to learn how we can help.